The Europe predictive maintenance market is expected to grow from US$ 1,822.92 million in 2022 to US$ 7,644.05 million by 2028. It is estimated to grow at a CAGR of 27.0% from 2022 to 2028.
Rising Prevalence of Industry 4.0
Industry 4.0 is revolutionizing the way companies make, improve, and sell their products. Aerospace, defense, transportation, and many industries implement latest technologies, including Internet of Things (IoT), cloud computing and analytics, artificial intelligence (AI), and machine learning (ML), to improve processes and overall operations. The industries adopt these technologies to automate time-consuming processes, use AI to make informed decisions, and use cloud services to streamline data management. Companies in the oil & gas industry are significantly adopting technologies, such as IoT and advanced analytics, to enhance operational efficiencies, cut costs, and optimize manual processes. The oil and gas companies experience several unplanned incidences such as pipe leakage, energy grid failure among others which cost millions to the company. Predictive maintenance enables these companies to rely on Industrial Internet of Things (IIoT)-enabled technologies, such as sensor data, and use predictive analytics for real-time equipment inspections, which helps reduce maintenance costs and unplanned equipment downtime. Further, the use of UAVs, such as drones, has significantly disrupted the oil & gas industry by removing the need for manual inspections of the pipelines in difficult-to-access locations. The UAVs are beneficial in dangerous situations, such as gas leaks, and support early detection through instant data collection and transfer. Hence, the benefits associated with using predictive analytics and UAVs boost the predictive maintenance market. In the manufacturing industry, manufacturers had to rely on a reactive maintenance model to repair only after a failure of unit, which caused high cost of maintenance and paralyzed long periods of unscheduled downtime. Hence, these factors inevitably led to a lower quality output produced. With predictive maintenance models integrated into IoT and IIoT, the manufacturing industry players can significantly reduce costs by eliminating the need for unnecessarily frequent maintenance. Hence, manufacturing companies are comprehensively integrating predictive maintenance models to identify and predict potential problems given the specific information extracted from each unit, thereby maintaining overall manufacturing health in the process. As a result, the rising prevalence of industry 4.0 coupled with the growing manufacturing units across the world drives the growth of the predictive maintenance market.
Market Overview
Europe is segmented into Germany, France, Italy, the UK, Russia, and rest of Europe. The predictive maintenance is cheaper and integrating more powerful sensors, and big data analytics offer an unprecedented opportunity to track machine-tool performance and health conditions. However, as per the European Commission, manufacturers only spend 15% of their total maintenance costs on predictive (vs reactive or preventative) maintenance, which is expected to hold the potential opportunity for the growth of predictive maintenance across various industries in Europe. The digital transformation in Europe enables to leverage the advanced digital technologies such as IoT, AI, Big Data, and others to drive efficiencies and thereby open up new opportunities for the same, which involve digital twins that evidently improve the efficiency of predictive maintenance of the critical assets and thereby mitigating the exposure of hazardous environment to the workers in the facilities. Europe's oil & gas industry is leading the energy sectors added with an increased focus on enhancing efficiencies and reducing downtime, aiding the need for predictive maintenance. Predictive maintenance uses data, such as temperature, vibration, and throughput, collected by sensors, then analyzed for any red flags or abnormal results. The growing adoption of advanced technology for predictive maintenance is improving the facility's operational efficiency, which is augmenting the demand for predictive maintenance propelling the market growth over the forecast period. For instance, in June 2021, Dietsmann Smart Labs established a strategic partnership with Norwegian Data Analytics specialist Arundo for breakthrough development with an integrated predictive maintenance software solution for an industrial plant.
Europe Predictive Maintenance Market Segmentation
The Europe predictive maintenance market is segmented based on component, deployment type, technique, industry, and country.
General Electric Company; Hitachi, Ltd.; IBM Corporation; Microsoft Corporation; PTC Inc.; SAS Institute, Inc.; Schneider Electric SE; Software AG; and Syncron AB are the leading companies operating in the Europe predictive maintenance market.